In wireless communication, it is often desirable to reduce intersymbol interference to allow recovery of transmitted symbols. Due to time-varying properties of a communication channel, an adaptive equalizer is often used.
There exist several algorithms for adaptive equalization to deal with time-varying channels such as least mean squares (LMS) and recursive least squares (RLS) algorithms as described in Haykin, S., “Adaptive filter theory”, Prentice-Hall, 2002. However, their performance degrades in channels having a large eigenvalue spread. Recently, particle swarm optimization (PSO) has been used for adaptive estimation/equalization problems and showed its improved performance when compared with other conventional algorithms as described in Krusienski, D. J., and Jenkins, W. K., “The application of particle swarm optimization to adaptive IIR phase equalization”, ICASSP, Montreal, Quebec, Canada, May 2004, pp. 693-696, Liu, H., and Li, J., “A particle swarm optimization-based multiuser detection for receive-diversity-aided STBC systems”, IEEE Signal Process. Lett., 2008, 15, (3), pp. 29-32, and Al-Awami, A. T., Zerguine, A., Cheded, L., Zidouri, A., and Saif, W., “A new modified particle swarm optimization algorithm for adaptive equalization”, Digital Signal process., 2011, 21, pp. 195-207.
The foregoing “background” description is for the purpose of generally presenting the context of the disclosure. Work of the inventor, to the extent it is described in this background section, as well as aspects of the description which may not otherwise qualify as prior art at the time of filing, are neither expressly or impliedly admitted as prior art against the present invention. The foregoing paragraphs have been provided by way of general introduction, and are not intended to limit the scope of the following claims. The described embodiments, together with further advantages, will be best understood by reference to the following detailed description taken in conjunction with the accompanying drawings.